Mathematical modeling and optimal control of chagas disease transmission in evolving ecological environments

Abstract

Chagas disease remains a major public health challenge in many endemic regions due to sustained transmission among humans, animal reservoirs, and Triatomine bug vectors. In this study, we develop and analyze an eleven-compartment deterministic model describing the transmission dynamics of Trypanosoma cruzi among human, reservoir, and vector populations. The basic reproduction number is derived, and sensitivity analysis is performed to identify the parameters that most strongly influence disease transmission. An optimal control framework is then formulated to evaluate vector control, reservoir management, human screening and treatment, and housing improvement interventions. Numerical simulations show that integrated intervention strategies substantially reduce disease burden compared to single-control approaches. Cost-effectiveness analysis reveals that reservoir-only control is the most cost-effective strategy, whereas the combined reservoir–housing intervention achieves the greatest reduction in infections. These findings provide quantitative insights for designing efficient and sustainable Chagas disease control programs, particularly in resource-limited endemic settings.